Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, MD, 21702-5010, USA.
Integrative Systems Biology Program, US Army Center for Environmental Health Research, 568 Doughten Drive, Fort Detrick, MD, 21702-5010, USA.
BMC Bioinformatics. 2018 Nov 29;19(1):458. doi: 10.1186/s12859-018-2494-6.
Network medicine aims to map molecular perturbations of any given diseases onto complex networks with functional interdependencies that underlie a pathological phenotype. Furthermore, investigating the time dimension of disease progression from a network perspective is key to gaining key insights to the disease process and to identify diagnostic or therapeutic targets. Existing platforms are ineffective to modularize the large complex systems into subgroups and consolidate heterogeneous data to web-based interactive animation.
We have developed PanoromiX platform, a data-agnostic dynamic interactive visualization web application, enables the visualization of outputs from genome based molecular assays onto modular and interactive networks that are correlated with any pathophenotypic data (MRI, Xray, behavioral, etc.) over a time course all in one pane. As a result, PanoromiX reveals the complex organizing principles that orchestrate a disease-pathology from a gene regulatory network (nodes, edges, hubs, etc.) perspective instead of snap shots of assays. Without extensive programming experience, users can design, share, and interpret their dynamic networks through the PanoromiX platform with rich built-in functionalities.
This emergent tool of network medicine is the first to visualize the interconnectedness of tailored genome assays to pathological networks and phenotypes for cells or organisms in a data-agnostic manner. As an advanced network medicine tool, PanoromiX allows monitoring of panel of biomarker perturbations over the progression of diseases, disease classification based on changing network modules that corresponds to specific patho-phenotype as opposed to clinical symptoms, systematic exploration of complex molecular interactions and distinct disease states via regulatory network changes, and the discovery of novel diagnostic and therapeutic targets.
网络医学旨在将任何给定疾病的分子扰动映射到具有功能相互依存关系的复杂网络上，这些关系是病理表型的基础。此外，从网络角度研究疾病进展的时间维度是深入了解疾病过程和识别诊断或治疗靶点的关键。现有的平台无法将大型复杂系统模块化，并将异构数据整合到基于网络的交互式动画中。
我们开发了 PanoromiX 平台，这是一个数据不可知的动态交互式可视化网络应用程序，它能够将基于基因组的分子分析的输出可视化到模块化和交互式网络上，这些网络与任何病理表型数据（MRI、X 射线、行为等）相关联，并在一个窗格中随时间推移进行。因此，PanoromiX 从基因调控网络（节点、边缘、枢纽等）的角度揭示了协调疾病-病理学的复杂组织原则，而不是分析的快照。无需广泛的编程经验，用户可以通过 PanoromiX 平台设计、共享和解释他们的动态网络，该平台具有丰富的内置功能。
作为网络医学的新兴工具，PanoromiX 是第一个以数据不可知的方式可视化定制基因组分析与细胞或生物体病理网络和表型的相互联系。作为一种先进的网络医学工具，PanoromiX 允许监测疾病进展过程中生物标志物扰动的面板，根据与特定病理表型相对应的变化网络模块对疾病进行分类，而不是根据临床症状，通过调节网络变化系统地探索复杂的分子相互作用和不同的疾病状态，以及发现新的诊断和治疗靶点。
